Aspectual Classifications: Use of Raters’ Associations and Co-occurrences of Verbs for Aspectual Classification in German

  • Michael RichterEmail author
  • Jürgen Hermes
  • Claes Neuefeind
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11352)


The present study examines the results of experiments on the automatic classification of German verbs into five aspectual classes [1]: An experiment within an unsupervised framework based on associations of raters [1] and a couple of experiments within a distributional framework, i.e. in window-based and in a subcategorization-frame-based approach [2]. We compare the predictive power of raters’ associations against two types of verbal cooccurrences: i. pure, unstructured co-occurrences and ii. linguistically motivated, well defined co-occurrences which we denote as informed distributional framework. We observed substantial (unsupervised) and excellent (supervised) agreements with a Gold Standard classification.


Machine learning Classification Aspectual verb classes Unsupervised learning Supervised learning 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Michael Richter
    • 1
    Email author
  • Jürgen Hermes
    • 2
  • Claes Neuefeind
    • 2
  1. 1.Department of Automatic Language ProcessingLeipzig UniversityLeipzigGermany
  2. 2.Institute for Digital Humanities, Cologne University, Albertus-Magnus-PlatzCologneGermany

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